Evidence map›Paper›PMID 38348112›Full record

ArticleFrontiers in neurology2023

Quantified fat fraction as biomarker assessing disease severity in rare Charcot-Marie-Tooth subtypes.

Xingwen Sun, Xiaoxuan Liu, Qiang Zhao, Lihua Zhang, Huishu Yuan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Xingwen Sun *Department of Radiology, Peking University Third Hospital, Beijing, China.
Xiaoxuan Liu *Department of Neurology, Peking University Third Hospital, Beijing, China.
Qiang Zhao *Department of Radiology, Peking University Third Hospital, Beijing, China.
Lihua ZhangDepartment of Radiology, Peking University Third Hospital, Beijing, China.
Huishu YuanDepartment of Radiology, Peking University Third Hospital, Beijing, China.
Peking University Third Hospital · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Charcot-Marie-Tooth (CMT) disease is the most common inherited neuromuscular disorder. Multi-echo Dixon MRI technique is a highly sensitive method for quantifying muscle fatty infiltration, which may provide excellent value for the assessment of CMT. Due to the rareness of the disease, its use in CMT disease has been rarely evaluated, especially in subtypes. Methods: Thirty-four CMT1 patients, 25 CMT2 patients, and 10 healthy controls were recruited. All of the recruited CMT1 patients are CMT1A with PMP22 duplication. Among CMT2 patients, 7 patients are CMT2A with MFN2 mutation, and 7 patients have SORD mutations. Multi-echo Dixon MRI imaging was performed. The fat fractions (FFs) of 5 muscle compartments of the leg were measured at proximal, middle, and distal levels by two specialized musculoskeletal radiologists. Comparisons between CMT1, CMT2, and genetically defined subtypes were conducted. Results: A proximal-distal gradient (27.6 ± 15.9, 29.9 ± 19.7, and 40.5 ± 21.4, Discussion: Multi-echo Dixon MRI imaging is a valuable tool for assessing disease severity in CMT. The difference in patterns of fatty infiltration of CMT subtypes is first reported, which could provide references when making targeted training plans.

Indexed as

calf musclesCharcot–Marie–Tooth diseasefat fractionmagnetic resonance imagingmuscle fat quantification

Identifiers

PMID38348112
PMCPMC10859536
OpenAlexW4391321385

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.